Repository: mckelvin/beancount-boilerplate-cn Branch: dev Commit: f250b25c2a05 Files: 27 Total size: 298.9 KB Directory structure: gitextract_4wi0e4ne/ ├── .gitignore ├── .python-version ├── Makefile ├── README.md ├── importers/ │ └── spdccc_importer.py ├── ledger/ │ ├── account.beancount │ ├── commodity.beancount │ ├── cryptocoin.beancount │ ├── daily/ │ │ ├── 2019/ │ │ │ ├── 2019-06-03-other.beancount │ │ │ ├── 2019-06-03-settle.beancount │ │ │ └── 2019-06-03-spdbcc.beancount │ │ └── 2019.beancount │ ├── init.beancount │ ├── invest.beancount │ ├── main.beancount │ ├── prices.beancount │ └── salary.beancount ├── raw-data/ │ └── spdbcc/ │ └── 2019-05-spdbcc.csv ├── requirements.in ├── requirements.txt ├── scripts/ │ ├── README.md │ ├── generate-networth-report.py │ ├── generate-portfolio.py │ └── update-prices.py └── sources/ ├── eastmoney.py ├── exchangeratesapi.py └── xueqiu.py ================================================ FILE CONTENTS ================================================ ================================================ FILE: .gitignore ================================================ __pycache__/ .py[oc] ledger/latest-prices.beancount local/ ================================================ FILE: .python-version ================================================ beancount-env ================================================ FILE: Makefile ================================================ GDOCIDFILE=local/gdocid GDOCID=`cat $(GDOCIDFILE)` TODAY=`date "+%Y-%m-%d"` MONTH=`date "+%Y-%m"` DIARY_MD_PATH=`date "+raw-data/.notable/notes/diary/%Y/%m/%Y-%m-%d.md"` PFCSV="local/portfolio-$(TODAY).csv" NWCSV="local/net-worth-$(TODAY).csv" all: prices prices-today: ./scripts/update-prices.py --today-only | sh prices: ./scripts/update-prices.py | sh fava: fava ledger/main.beancount %: bean-$@ ledger/main.beancount portfolio: @./scripts/generate-portfolio.py networth: @./scripts/generate-networth-report.py gdocid: @test -f $(GDOCIDFILE) && true || (echo "Please fill gdoc id in $(GDOCIDFILE)"; exit 1) spreadsheet: gdocid @echo "Generating $(PFCSV) ..." @./scripts/generate-portfolio.py > $(PFCSV) @echo "$(PFCSV) Done\n" @echo "Generating $(NWCSV) ..." @./scripts/generate-networth-report.py --padding --since 2019-10-01 > $(NWCSV) @echo "$(NWCSV) Done\n" @egrep "^(日期|$(MONTH))" $(NWCSV) | column -ts, @echo "Uploading to spreadsheet ..." @upload-to-sheets --docid=$(GDOCID) $(PFCSV):持仓 $(NWCSV):净值 today: make prices-today make spreadsheet backup: git stash git pull --rebase origin master git stash pop git add . git commit -m "AutoBackup" git push origin master ================================================ FILE: README.md ================================================ # beancount-boilerplate-cn 本项目是为如下人士准备的 (AND) - 生活、工作在中国 - 熟练使用 \*nix 环境下终端操作 - 对[文本记账](https://plaintextaccounting.org/)感兴趣 - 看过了最基础的 beancount 介绍但是没有看完所有文档（太多了） - 想马上试试用 beancount 记账 ### 安装 1. Python 3.6.5 # Python3 就行 如果你已经安装了 [pyenv-virtualenv](https://github.com/pyenv/pyenv-virtualenv), 那需要一个基于 Python 3.6.5 的虚拟环境，否则请自行准备 Python 3.6.5 运行环境: ```shell pyenv virtualenv 3.6.5 beancount-env ``` 2. 安装依赖的库 ```shell pip install -r requirements.txt ``` ### 这份模板中的假定使用者是这样的: - 有如下银行的储蓄卡 - 招商银行 (工资卡) - 招商银行香港分行 - 有如下银行的全币种信用卡 - 浦发银行 (日常消费主力卡, 外币交易自动购汇人民币还款) - 工商银行 (境外消费为主，外币交易不自动购汇，需要自行购汇还外币) - 有如下投资(机)账户 - 富途证券港美股账户 - 东方财富证券A股账户 - 蚂蚁财富(支付宝)基金账户 - 天天基金账户 ### 如何查看报表 1. 在 https://docs.google.com/spreadsheets 新建一个表格，复制URL中的ID部分到`local/gdocid` 这个文件中。 ```bash # 比如 https://docs.google.com/spreadsheets/d/1jnds3X_-RSTN4ATuOFV-v6tar0KfAla88vC43Vq6ubc/edit?usp=sharing $ cat local/gdocid 1jnds3X_-RSTN4ATuOFV-v6tar0KfAla88vC43Vq6ubc ``` 2. `make prices` 确认标的价格是最新的 3. `make spreadsheets` 生成净值和持仓csv文件，并上传到上述新建的spreadsheet. 期间可能会提示配置 Google Docs 的 API Key, 按提示进行即可。 4. `净值`和`持仓`分别会出现在2个sheet里，如果需要报表的话，可以基于这些数据新建一个sheet放报表。举个例子： [![](https://raw.githubusercontent.com/mckelvin/beancount-boilerplate-cn/dev/.github/screenshot/report-demo.png)](https://docs.google.com/spreadsheets/d/1jnds3X_-RSTN4ATuOFV-v6tar0KfAla88vC43Vq6ubc/edit#gid=0) ### 如何初始化/已有帐本迁移过来 可见 `ledger/init.beancount` 文件中初始化的过程 ### Commodity 命名 每一个投资标的就是一个commodity, 比如现金 CNY, USD, 股票 SPY, AAPL ... - 各国外汇按标准名称来： - `CNY`, `USD`, `CNH`, ... - 美股代号按交易所代码来 - `AAPL`, `GOOGL` - 港股代号以 `HK_` 开头按 4 位数字命名 - `HK_2800`, `HK_0700` - A股(含场内基金)代号以 `CN_` 开头按 6 位数字命名 - `CN_000001`, `CN_510300`, ... - 场外基金(货币基金除外)以 `CN_F` 开头按 6 位数字命名 - `CN_F110011` - 货币基金直接用 CNY 表示，收益需要手工更新(原因是货币基金无净值的概念)。 - CNY ### 你可能想批量替换的关键字 - 帐本名称 `YourLedger` - 所在城市 `YourCity` - 供职单位 `YourEmployer` - `XXX` - `TODO` ### 文件布局 - importers/ : 通过 bean-extract 自动导入帐单所需的自定义脚本 - raw-data/ : csv 等格式的原始帐单存放目录 - sources/ : 自定义的股票、基金行情脚本（默认只支持从雅虎财经中获取） - ledger/ : 所有的 beancount 文件都在这里面 - main.beancount : 主入口 - account.beancount : 所有的账户定义在这里 - commodity.beancount : 如果你不需要自动获取行情价格，你甚至都不需要这个文件 - prices.beancount : 这个文件由 bean-price 命令管理，一般不需要手动修改 - init.beancount : 初始化帐本用 - salary.beancount : 工资收入 - invest.beancount : 现金之外的投资(机)相关记录(买卖、申赎) - daily/ : 日常流水 - daily/2019 : 按年分目录 - daily/2019/2019-07-03-spdbccc.beancount : 主力消费卡记录(自动生成+人工修改) - daily/2019/2019-07-03-other.beancount : 非主力下记录 - daily/2019/2019-07-03-settle.beancount : 定期结算检查点 ### 支出如何分类 - 参照随手记App的支出分类法, 分为2级, 见 ledger/account.beancount 中账户的定义。 ### 如何处理五险一金 - 公司缴纳的公积金作为收入计算 - 公司缴纳的各种险不入帐 - 个人缴纳的各种税和险作为支出计算 - 个人缴纳的公积金当作转帐计算 - 详见 salary.beancount ### 如何处理股票、基金 - 因为交易频率不高，因此数据都是手工输入 - 可参见 invest.beancount 中的定义 ### 如何获取外汇、股票、基金行情 - ledger/commodity.beancount 中定义了某一个 commodity 从哪里获取行情 - 自定义行情脚本定义在 sources/ , 目前支持从雪球获取A/港/美股股票行情，从天天基金获取基金行情 - 货币基金当现金处理 ### 如何获取标的的最新价格 ``` make prices # 或 ./scripts/update-prices.py | sh ``` 这个命令会自动拉取最后一条 price 记录的时间到昨天为止的各个持仓标的的价格。建议隔三差五就跑一次。 ### 如何自动生成帐单 基于2019年5月的帐单(csv格式)生成 beancount 文件 ``` bean-extract importers/spdccc_importer.py raw-data/spdbcc/2019-05-spdbcc.csv > ledger/daily/2019/2019-06-03-spdbcc.beancount ``` ### 如何加密帐单信息 当前仓库默认没有加密，如果你想加密的话，推荐使用 [git-crypt](https://github.com/AGWA/git-crypt), 它比 [git-secret](https://git-secret.io/) 使用起来更加方便。 ### 如何查看当前和历史持仓 ``` ./scripts/generate-portfolio.py -d 2019-12-31 # 查看某一日的持仓 ./scripts/generate-portfolio.py # 查看当前持仓 ``` 输出的csv格式持仓可以[导入表格软件](https://bitbucket.org/blais/beancount/src/default/beancount/tools/sheets_upload.py)进一步分析，或者使用 [tabview](https://pypi.org/project/tabview/) 直接在终端浏览。例子: |一级类别|二级类别 |标的 |代号 |持仓量 |市场价格 |报价日期 |市场价值 |货币 |人民币价值 |占比 | |----|------|----------------|----------|----------|---------|----------|------|----|---------|------| |现金 |本币 |人民币 |CNY |59287.860 |1.0000 | |59288 |CNY |59287.86 |10.68%| |现金 |外汇 |美元 |USD |19460.700 |1.0000 | |19461 |USD |138338.94|24.92%| |现金 |外汇 |港元 |HKD |134112.000|1.0000 | |134112|HKD |123000.76|22.16%| |现金 |外汇 |离岸人民币 |CNH |1000.000 |1.0000 | |1000 |CNH |999.20 |0.18% | |债权 |债券基金 |华泰柏瑞丰盛纯债债券A |CN_F000187|6000.000 |1.2902 |2020-05-15|7741 |CNY |7741.20 |1.39% | |债权 |可转换债券 |光电转债 |CN_128047 |100.000 |129.0270 |2019-10-15|12903 |CNY |12902.70 |2.32% | |股权 |指数基金 |SPDR S&P 500 ETF|SPY |15.000 |286.2800 |2020-05-15|4294 |USD |30525.88 |5.50% | |股权 |指数基金 |华泰沪深300ETF |CN_510300 |100.000 |3.9020 |2020-05-15|390 |CNY |390.20 |0.07% | |股权 |偏股混合基金|易方达中小盘混合 |CN_F110011|10000.000 |5.2343 |2020-05-15|52343 |CNY |52343.00 |9.43% | |股权 |A股 |平安银行 |CN_000001 |100.000 |13.2300 |2020-05-15|1323 |CNY |1323.00 |0.24% | |股权 |港股 |腾讯控股 |HK_0700 |50.000 |421.2000 |2020-05-15|21060 |HKD |19315.17 |3.48% | |股权 |港股 |盈富基金 |HK_2800 |100.000 |24.0000 |2020-05-15|2400 |HKD |2201.16 |0.40% | |股权 |美股 |Apple Inc. |AAPL |10.000 |307.7100 |2020-05-15|3077 |USD |21873.97 |3.94% | |另类 |加密货币 |USDT |USDT |776.340 |1.0000 | |776 |USDT|5395.56 |0.97% | |另类 |加密货币 |比特币 |BTC |1.175 |9336.9561|2020-05-15|10967 |USD |77958.38 |14.04%| |另类 |加密货币 |以太坊 |ETH |1.000 |223.8500 |2019-07-16|224 |USDT|1555.76 |0.28% | ### 如何查看投资净值 ``` ./scripts/generate-networth-report.py # 查看年初至今的净值 ./scripts/generate-networth-report.py -s 2019-12-01 # 查看某一日至今的净值 ``` 输出的csv格式持仓可以[导入表格软件](https://bitbucket.org/blais/beancount/src/default/beancount/tools/sheets_upload.py)进一步分析，或者使用 [tabview](https://pypi.org/project/tabview/) 直接在终端浏览。例子: |日期 |净资产 |可投资金额 |非投资收入 |非投资支出 |投资盈亏 |投资盈亏% |累计净值 |累计盈亏|当年净值 |当年盈亏 |另类% |股权% |债权% |现金% | |---|------|----------------|----------|----------|---------|----------|------|----|---------|------|------|------|-----|------| |2020-01-01|559138.53|531175.73 |0.00 |0.00 |n/a |n/a |1.0000|0.00|1.0000 |0.00 |13.20%|23.54%|3.84%|59.43%| |2020-01-02|558641.52|530678.72 |0.00 |0.00 |-497.01 |-0.0936% |0.9991|-497.01|0.9991 |-497.01|12.94%|23.73%|3.84%|59.49%| |2020-01-03|560789.32|532826.52 |0.00 |0.00 |2147.79 |0.4047% |1.0031|1650.79|1.0031 |1650.79|13.37%|23.47%|3.82%|59.33%| |2020-01-06|562714.79|534751.99 |0.00 |0.00 |1925.47 |0.3614% |1.0067|3576.26|1.0067 |3576.26|13.87%|23.17%|3.81%|59.15%| |2020-01-07|564344.69|536381.89 |0.00 |0.00 |1629.91 |0.3048% |1.0098|5206.16|1.0098 |5206.16|14.30%|23.14%|3.80%|58.76%| |2020-01-08|563946.82|535984.02 |0.00 |0.00 |-397.87 |-0.0742% |1.0091|4808.29|1.0091 |4808.29|14.20%|23.19%|3.80%|58.81%| |2020-01-09|563990.03|536027.23 |0.00 |0.00 |43.20 |0.0081% |1.0091|4851.49|1.0091 |4851.49|13.92%|23.54%|3.80%|58.74%| |2020-01-10|566470.03|538507.23 |0.00 |0.00 |2480.00 |0.4627% |1.0138|7331.50|1.0138 |7331.50|14.21%|23.59%|3.79%|58.41%| |2020-01-13|566349.87|538387.07 |0.00 |0.00 |-120.16 |-0.0223% |1.0136|7211.34|1.0136 |7211.34|14.14%|23.87%|3.79%|58.20%| |2020-01-14|569554.58|541591.78 |0.00 |0.00 |3204.72 |0.5952% |1.0196|10416.05|1.0196 |10416.05|14.92%|23.52%|3.77%|57.80%| |2020-01-15|569552.86|541590.06 |0.00 |0.00 |-1.73 |-0.0003% |1.0196|10414.33|1.0196 |10414.33|14.89%|23.51%|3.77%|57.83%| |2020-01-16|569231.86|541269.06 |0.00 |0.00 |-320.99 |-0.0593% |1.0190|10093.33|1.0190 |10093.33|14.78%|23.64%|3.77%|57.80%| |2020-01-17|569877.74|541914.94 |0.00 |0.00 |645.88 |0.1193% |1.0202|10739.21|1.0202 |10739.21|14.99%|23.64%|3.77%|57.60%| |2020-01-20|568368.80|540406.00 |0.00 |0.00 |-1508.94 |-0.2784% |1.0174|9230.27|1.0174 |9230.27|14.70%|23.70%|3.78%|57.82%| |2020-01-21|569909.61|541946.81 |0.00 |0.00 |1540.81 |0.2851% |1.0203|10771.08|1.0203 |10771.08|14.83%|23.50%|3.77%|57.90%| |2020-01-22|569567.31|541604.51 |0.00 |0.00 |-342.30 |-0.0632% |1.0196|10428.78|1.0196 |10428.78|14.76%|23.55%|3.77%|57.92%| |2020-01-23|567857.58|539894.78 |0.00 |0.00 |-1709.73 |-0.3157% |1.0164|8719.05|1.0164 |8719.05|14.50%|23.40%|3.78%|58.32%| |2020-01-24|567857.58|539894.78 |0.00 |0.00 |0.00 |0.0000% |1.0164|8719.05|1.0164 |8719.05|14.50%|23.40%|3.78%|58.32%| |2020-01-27|567857.58|539894.78 |0.00 |0.00 |0.00 |0.0000% |1.0164|8719.05|1.0164 |8719.05|14.50%|23.40%|3.78%|58.32%| |2020-01-28|567857.58|539894.78 |0.00 |0.00 |0.00 |0.0000% |1.0164|8719.05|1.0164 |8719.05|14.50%|23.40%|3.78%|58.32%| |2020-01-29|567857.58|539894.78 |0.00 |0.00 |0.00 |0.0000% |1.0164|8719.05|1.0164 |8719.05|14.50%|23.40%|3.78%|58.32%| |2020-01-30|567857.58|539894.78 |0.00 |0.00 |0.00 |0.0000% |1.0164|8719.05|1.0164 |8719.05|14.50%|23.40%|3.78%|58.32%| |2020-01-31|567857.58|539894.78 |0.00 |0.00 |0.00 |0.0000% |1.0164|8719.05|1.0164 |8719.05|14.50%|23.40%|3.78%|58.32%| |2020-02-03|573898.42|545935.62 |0.00 |0.00 |6040.84 |1.1189% |1.0278|14759.89|1.0278 |14759.89|15.61%|22.36%|3.75%|58.27%| |2020-02-04|574237.05|546274.25 |0.00 |0.00 |338.63 |0.0620% |1.0284|15098.52|1.0284 |15098.52|15.42%|22.75%|3.75%|58.08%| |2020-02-05|577799.49|549836.69 |0.00 |0.00 |3562.44 |0.6521% |1.0351|18660.96|1.0351 |18660.96|15.83%|22.89%|3.73%|57.55%| |2020-02-06|580439.96|552477.16 |0.00 |0.00 |2640.47 |0.4802% |1.0401|21301.43|1.0401 |21301.43|15.89%|23.15%|3.71%|57.25%| |2020-02-07|580439.96|552477.16 |0.00 |0.00 |0.00 |0.0000% |1.0401|21301.43|1.0401 |21301.43|15.89%|23.15%|3.71%|57.25%| |2020-02-10|582205.63|554242.83 |0.00 |0.00 |1765.67 |0.3196% |1.0434|23067.10|1.0434 |23067.10|16.03%|23.12%|3.70%|57.16%| |2020-02-11|585175.01|557212.21 |0.00 |0.00 |2969.38 |0.5358% |1.0490|26036.48|1.0490 |26036.48|16.37%|23.16%|3.68%|56.79%| |2020-02-12|586760.25|558797.45 |0.00 |0.00 |1585.24 |0.2845% |1.0520|27621.72|1.0520 |27621.72|16.46%|23.27%|3.67%|56.60%| |2020-02-13|586547.84|558585.04 |0.00 |0.00 |-212.41 |-0.0380% |1.0516|27409.31|1.0516 |27409.31|16.35%|23.26%|3.67%|56.71%| |2020-02-14|587939.30|559976.50 |0.00 |0.00 |1391.45 |0.2491% |1.0542|28800.77|1.0542 |28800.77|16.44%|23.30%|3.67%|56.59%| |2020-02-17|583519.50|555556.70 |0.00 |0.00 |-4419.79 |-0.7893% |1.0459|24380.97|1.0459 |24380.97|15.78%|23.52%|3.70%|57.01%| |2020-02-18|586376.83|558414.03 |0.00 |0.00 |2857.33 |0.5143% |1.0513|27238.30|1.0513 |27238.30|16.30%|23.18%|3.68%|56.84%| |2020-02-19|586376.83|558414.03 |0.00 |0.00 |0.00 |0.0000% |1.0513|27238.30|1.0513 |27238.30|16.30%|23.18%|3.68%|56.84%| |2020-02-20|585097.66|557134.86 |0.00 |0.00 |-1279.16 |-0.2291% |1.0489|25959.13|1.0489 |25959.13|15.70%|23.53%|3.69%|57.08%| |2020-02-21|584653.91|556691.11 |0.00 |0.00 |-443.75 |-0.0796% |1.0480|25515.38|1.0480 |25515.38|15.83%|23.32%|3.69%|57.16%| |2020-02-24|581216.57|553253.77 |0.00 |0.00 |-3437.34 |-0.6175% |1.0416|22078.04|1.0416 |22078.04|15.89%|22.88%|3.72%|57.52%| |2020-02-25|576706.02|548743.22 |0.00 |0.00 |-4510.55 |-0.8153% |1.0331|17567.49|1.0331 |17567.49|15.59%|22.79%|3.75%|57.87%| |2020-02-26|572481.47|544518.67 |0.00 |0.00 |-4224.55 |-0.7699% |1.0251|13342.94|1.0251 |13342.94|15.04%|22.84%|3.78%|58.34%| |2020-02-27|569084.25|541121.45 |0.00 |0.00 |-3397.22 |-0.6239% |1.0187|9945.72|1.0187 |9945.72|15.07%|22.52%|3.80%|58.61%| |2020-02-28|564817.25|536854.45 |0.00 |0.00 |-4267.00 |-0.7885% |1.0107|5678.72|1.0107 |5678.72|15.01%|22.23%|3.83%|58.93%| |2020-03-02|569944.19|541981.39 |0.00 |0.00 |5126.95 |0.9550% |1.0203|10805.66|1.0203 |10805.66|15.09%|22.83%|3.80%|58.29%| |2020-03-03|569387.90|541425.10 |0.00 |0.00 |-556.29 |-0.1026% |1.0193|10249.37|1.0193 |10249.37|15.02%|22.74%|3.80%|58.44%| |2020-03-04|568808.58|540845.78 |0.00 |0.00 |-579.32 |-0.1070% |1.0182|9670.05|1.0182 |9670.05|14.90%|23.14%|3.81%|58.15%| |2020-03-05|572248.46|544285.66 |0.00 |0.00 |3439.87 |0.6360% |1.0247|13109.93|1.0247 |13109.93|15.24%|23.12%|3.78%|57.86%| |2020-03-06|569850.80|541888.00 |0.00 |0.00 |-2397.66 |-0.4405% |1.0202|10712.26|1.0202 |10712.26|15.35%|22.79%|3.80%|58.06%| |2020-03-09|556295.99|528333.19 |0.00 |0.00 |-13554.81|-2.5014% |0.9946|-2842.54|0.9946 |-2842.54|14.21%|22.20%|3.90%|59.70%| |2020-03-10|560642.04|532679.24 |0.00 |0.00 |4346.06 |0.8226% |1.0028|1503.51|1.0028 |1503.51|14.09%|22.77%|3.87%|59.28%| |2020-03-11|557566.89|529604.09 |0.00 |0.00 |-3075.15 |-0.5773% |0.9970|-1571.64|0.9970 |-1571.64|14.16%|22.37%|3.89%|59.58%| |2020-03-12|533753.00|505790.20 |0.00 |0.00 |-23813.90|-4.4965% |0.9522|-25385.54|0.9522 |-25385.54|10.85%|22.25%|4.07%|62.83%| |2020-03-13|540151.97|512189.17 |0.00 |0.00 |6398.98 |1.2651% |0.9643|-18986.56|0.9643 |-18986.56|11.50%|22.62%|4.02%|61.87%| |2020-03-16|529322.49|501359.69 |0.00 |0.00 |-10829.48|-2.1144% |0.9439|-29816.04|0.9439 |-29816.04|11.01%|21.42%|4.10%|63.46%| |2020-03-17|533129.86|505167.06 |0.00 |0.00 |3807.37 |0.7594% |0.9510|-26008.67|0.9510 |-26008.67|11.22%|21.73%|4.07%|62.98%| |2020-03-18|530493.16|502530.36 |0.00 |0.00 |-2636.70 |-0.5219% |0.9461|-28645.37|0.9461 |-28645.37|11.31%|21.18%|4.09%|63.42%| |2020-03-19|540071.63|512108.83 |0.00 |0.00 |9578.47 |1.9060% |0.9641|-19066.90|0.9641 |-19066.90|12.51%|20.67%|4.01%|62.81%| |2020-03-20|539069.72|511106.92 |0.00 |0.00 |-1001.91 |-0.1956% |0.9622|-20068.81|0.9622 |-20068.81|12.51%|20.69%|4.02%|62.78%| |2020-03-23|537334.85|509372.05 |0.00 |0.00 |-1734.87 |-0.3394% |0.9590|-21803.68|0.9590 |-21803.68|12.85%|20.17%|4.04%|62.95%| |2020-03-24|544602.16|516639.36 |0.00 |0.00 |7267.31 |1.4267% |0.9726|-14536.37|0.9726 |-14536.37|13.07%|21.05%|3.98%|61.89%| |2020-03-25|548926.96|520964.16 |0.00 |0.00 |4324.80 |0.8371% |0.9808|-10211.57|0.9808 |-10211.57|12.94%|21.46%|3.95%|61.65%| |2020-03-26|550531.93|522569.13 |0.00 |0.00 |1604.97 |0.3081% |0.9838|-8606.60|0.9838 |-8606.60|12.92%|21.85%|3.94%|61.29%| |2020-03-27|548513.85|520551.05 |0.00 |0.00 |-2018.09 |-0.3862% |0.9800|-10624.69|0.9800 |-10624.69|12.66%|21.69%|3.95%|61.69%| |2020-03-30|548359.00|520396.20 |0.00 |0.00 |-154.84 |-0.0297% |0.9797|-10779.53|0.9797 |-10779.53|12.62%|21.70%|3.96%|61.73%| |2020-03-31|549446.65|521483.85 |0.00 |0.00 |1087.65 |0.2090% |0.9818|-9691.88|0.9818 |-9691.88|12.60%|21.85%|3.95%|61.60%| |2020-04-01|548247.47|520284.67 |0.00 |0.00 |-1199.18 |-0.2300% |0.9795|-10891.06|0.9795 |-10891.06|12.86%|21.42%|3.96%|61.76%| |2020-04-02|548247.47|520284.67 |0.00 |0.00 |0.00 |0.0000% |0.9795|-10891.06|0.9795 |-10891.06|12.86%|21.42%|3.96%|61.76%| |2020-04-03|549544.74|521581.94 |0.00 |0.00 |1297.27 |0.2493% |0.9819|-9593.79|0.9819 |-9593.79|12.99%|21.53%|3.95%|61.53%| |2020-04-06|549544.74|521581.94 |0.00 |0.00 |0.00 |0.0000% |0.9819|-9593.79|0.9819 |-9593.79|12.99%|21.53%|3.95%|61.53%| |2020-04-07|555576.69|527613.89 |0.00 |0.00 |6031.95 |1.1565% |0.9933|-3561.84|0.9933 |-3561.84|13.39%|22.11%|3.91%|60.59%| |2020-04-08|558227.88|530265.08 |0.00 |0.00 |2651.19 |0.5025% |0.9983|-910.65|0.9983 |-910.65|13.55%|22.20%|3.89%|60.36%| |2020-04-09|558985.91|531023.11 |0.00 |0.00 |758.02 |0.1430% |0.9997|-152.62|0.9997 |-152.62|13.47%|22.42%|3.89%|60.21%| |2020-04-10|556044.40|528081.60 |0.00 |0.00 |-2941.50 |-0.5539% |0.9942|-3094.13|0.9942 |-3094.13|12.96%|22.57%|3.91%|60.55%| |2020-04-13|555767.48|527804.68 |0.00 |0.00 |-276.92 |-0.0524% |0.9937|-3371.05|0.9937 |-3371.05|12.94%|22.56%|3.91%|60.58%| |2020-04-14|558327.52|530364.72 |0.00 |0.00 |2560.03 |0.4850% |0.9985|-811.02|0.9985 |-811.02|12.88%|22.95%|3.89%|60.28%| |2020-04-15|556094.93|528132.13 |0.00 |0.00 |-2232.59 |-0.4210% |0.9943|-3043.61|0.9943 |-3043.61|12.67%|22.85%|3.91%|60.57%| |2020-04-16|560659.12|532696.32 |0.00 |0.00 |4564.20 |0.8642% |1.0029|1520.59|1.0029 |1520.59|13.20%|22.80%|3.88%|60.12%| |2020-04-17|561653.16|533690.36 |0.00 |0.00 |994.03 |0.1866% |1.0047|2514.63|1.0047 |2514.63|13.15%|22.95%|3.87%|60.03%| |2020-04-20|559297.52|531334.72 |0.00 |0.00 |-2355.64 |-0.4414% |1.0003|158.99|1.0003 |158.99|12.93%|22.89%|3.89%|60.29%| |2020-04-21|557604.40|529641.60 |0.00 |0.00 |-1693.12 |-0.3187% |0.9971|-1534.13|0.9971 |-1534.13|12.99%|22.47%|3.90%|60.63%| |2020-04-22|561186.28|533223.48 |0.00 |0.00 |3581.88 |0.6763% |1.0039|2047.75|1.0039 |2047.75|13.20%|22.78%|3.88%|60.14%| |2020-04-23|563852.05|535889.25 |0.00 |0.00 |2665.77 |0.4999% |1.0089|4713.52|1.0089 |4713.52|13.55%|22.78%|3.86%|59.82%| |2020-04-24|565331.28|537368.48 |0.00 |0.00 |1479.23 |0.2760% |1.0117|6192.75|1.0117 |6192.75|13.67%|22.83%|3.85%|59.65%| |2020-04-27|568194.44|540231.64 |0.00 |0.00 |2863.16 |0.5328% |1.0170|9055.91|1.0170 |9055.91|13.92%|22.89%|3.83%|59.36%| |2020-04-28|569105.92|541143.12 |0.00 |0.00 |911.48 |0.1687% |1.0188|9967.39|1.0188 |9967.39|13.91%|23.05%|3.82%|59.22%| |2020-04-29|577034.26|549071.46 |0.00 |0.00 |7928.35 |1.4651% |1.0337|17895.73|1.0337 |17895.73|14.99%|22.88%|3.77%|58.36%| |2020-04-30|574514.61|546551.81 |0.00 |0.00 |-2519.65 |-0.4589% |1.0289|15376.08|1.0289 |15376.08|14.83%|22.94%|3.79%|58.44%| |2020-05-01|574514.61|546551.81 |0.00 |0.00 |0.00 |0.0000% |1.0289|15376.08|1.0289 |15376.08|14.83%|22.94%|3.79%|58.44%| |2020-05-04|574514.61|546551.81 |0.00 |0.00 |0.00 |0.0000% |1.0289|15376.08|1.0289 |15376.08|14.83%|22.94%|3.79%|58.44%| |2020-05-05|574514.61|546551.81 |0.00 |0.00 |0.00 |0.0000% |1.0289|15376.08|1.0289 |15376.08|14.83%|22.94%|3.79%|58.44%| |2020-05-06|581227.30|553264.50 |0.00 |0.00 |6712.69 |1.2282% |1.0416|22088.77|1.0416 |22088.77|15.51%|22.69%|3.74%|58.06%| |2020-05-07|586322.79|558359.99 |0.00 |0.00 |5095.49 |0.9210% |1.0512|27184.26|1.0512 |27184.26|16.21%|22.62%|3.70%|57.46%| |2020-05-08|586633.56|558670.76 |0.00 |0.00 |310.76 |0.0557% |1.0518|27495.03|1.0518 |27495.03|16.05%|22.91%|3.70%|57.35%| |2020-05-11|579773.30|551810.50 |0.00 |0.00 |-6860.25 |-1.2280% |1.0388|20634.77|1.0388 |20634.77|14.68%|23.39%|3.74%|58.19%| |2020-05-12|580085.90|552123.10 |0.00 |0.00 |312.60 |0.0567% |1.0394|20947.37|1.0394 |20947.37|14.92%|23.24%|3.74%|58.10%| |2020-05-13|583816.75|555853.95 |0.00 |0.00 |3730.85 |0.6757% |1.0465|24678.22|1.0465 |24678.22|15.42%|23.13%|3.71%|57.74%| |2020-05-14|588018.88|560056.08 |0.00 |0.00 |4202.13 |0.7560% |1.0544|28880.35|1.0544 |28880.35|15.92%|23.01%|3.69%|57.39%| |2020-05-15|584580.07|556617.27 |0.00 |0.00 |-3438.81 |-0.6140% |1.0479|25441.54|1.0479 |25441.54|15.52%|22.99%|3.71%|57.78%| |2020-05-18|584580.07|556617.27 |0.00 |0.00 |0.00 |0.0000% |1.0479|25441.54|1.0479 |25441.54|15.52%|22.99%|3.71%|57.78%| |2020-05-19|584580.07|556617.27 |0.00 |0.00 |0.00 |0.0000% |1.0479|25441.54|1.0479 |25441.54|15.52%|22.99%|3.71%|57.78%| |2020-05-20|584580.07|556617.27 |0.00 |0.00 |0.00 |0.0000% |1.0479|25441.54|1.0479 |25441.54|15.52%|22.99%|3.71%|57.78%| |2020-05-21|584580.07|556617.27 |0.00 |0.00 |0.00 |0.0000% |1.0479|25441.54|1.0479 |25441.54|15.52%|22.99%|3.71%|57.78%| |2020-05-22|584580.07|556617.27 |0.00 |0.00 |0.00 |0.0000% |1.0479|25441.54|1.0479 |25441.54|15.52%|22.99%|3.71%|57.78%| ================================================ FILE: importers/spdccc_importer.py ================================================ from beancount.ingest.importers import csv from beancount.core.data import Posting COMPACT_CATE_DICT = { "滴滴,嘀嘀,天津舒行科技,CAB": "Transport:Taxi", "药房,医院,医药,DRUG": "Health:Drugs", "交通卡,地铁,摩拜": "Transport:Public", "铁路,上铁": "Leisure:Train", "联合网络,中国移动": "Comm:PhonePlan", "宽带,VPS,Hosting": "Comm:Internet", "顺丰": "Comm:Express", "全家,便利,果品,果业,生鲜,水果": "Food:FruitSnacks", "餐厅,包子铺,名吃,小吃,餐饮,面馆," "盒马,豆浆": "Food:Meals", "优衣库": "Clothes:Clothes", "发型,美发": "Health:HairCutting", "AVIATION,航空": "Leisure:Aviation", "日上": "Leisure:Souvenir", "Smart2Pay B.V.": "Leisure:Gaming", "京东,宜家": "Home:Groceries", "电力公司": "Home:Utilities", "Spotify": "Leisure:Media", } CATE_DICT = { kw: cate_vals for kws, cate_vals in COMPACT_CATE_DICT.items() for kw in kws.split(",") } def _get_category(narration, default_cate="TODO"): for kw in CATE_DICT: if kw in narration: return CATE_DICT[kw] return default_cate def categorizer(txn): assert len(txn.postings) == 1, txn post = txn.postings[0] if post.units.number < 0: # 支出 category = _get_category(txn.narration) txn.postings.append(post._replace( account=f"Expenses:{category}", units=-post.units, )) elif post.units.number > 0: if "还款" in txn.narration: txn.postings.append(post._replace( account=f"Assets:CN:Saving:CMB:CNY", units=-post.units, )) else: extra_narration = " TODO" if "返现" in txn.narration: extra_narration = "" txn.postings.append(post._replace( account=post.account.replace("Liabilities", "Income"), units=-post.units, )) if extra_narration: txn = txn._replace(narration=txn.narration + extra_narration) return txn CONFIG = [ csv.Importer( { # 日期、金额等字段分别叫什么？ csv.Col.DATE: '记账日期', csv.Col.AMOUNT_DEBIT: '交易金额', csv.Col.NARRATION1: '交易描述', csv.Col.LAST4: '卡号末四位' }, # CSV文件中有哪几列？ regexps='卡号末四位,记账日期,交易金额,交易描述', account="Liabilities:CN:CreditCard:SPDB", currency='CNY', categorizer=categorizer, ) ] ================================================ FILE: ledger/account.beancount ================================================ ; 短期内不可用资产标记为 nondisposable:1 ; 不可退款的预付款标记为 sunk:1 * General Accounts 2000-01-01 open Equity:Openings-Balance CNY,USD,HKD,CNH,BTC,CN600519,AAPL,SPY,HK_2800,HK_0700,CN_510300,CN_000001,CN_128047,CN_F110011,CN_F000187,CN_510300 2000-01-01 open Expenses:Food:Meals name: "食品酒水/早中晚餐" 2000-01-01 open Expenses:Food:FruitSnacks name: "食品酒水/水果零食" 2000-01-01 open Expenses:Transport:Public name: "行车交通/公共交通" 2000-01-01 open Expenses:Transport:Taxi name: "休闲娱乐/打车租车" 2000-01-01 open Expenses:Leisure:Media name: "休闲娱乐/娱乐影音" 2000-01-01 open Expenses:Leisure:Study name: "休闲娱乐/学习进修" 2000-01-01 open Expenses:Leisure:Train name: "休闲娱乐/高铁旅行" 2000-01-01 open Expenses:Leisure:Aviation name: "休闲娱乐/飞机旅行" 2000-01-01 open Expenses:Leisure:Souvenir name: "休闲娱乐/旅行纪念品" 2000-01-01 open Expenses:Leisure:Gaming name: "休闲娱乐/游戏" 2000-01-01 open Expenses:Health:Drugs name: "医疗保健/药品费" 2000-01-01 open Expenses:Health:HairCutting name: "医疗保健/理发" 2000-01-01 open Expenses:Comm:PhonePlan name: "交流通讯/话费" 2000-01-01 open Expenses:Comm:Express name: "交流通讯/邮寄费" 2000-01-01 open Expenses:Comm:Internet name: "交流通讯/上网费" 2000-01-01 open Expenses:Comm:Registry name: "交流通讯/注册费" 2000-01-01 open Expenses:Clothes:Clothes name: "衣服饰品/衣服裤子" 2000-01-01 open Expenses:Home:Groceries name: "居家物业/生活用品" 2000-01-01 open Expenses:Home:Rental name: "居家物业/房租" 2000-01-01 open Assets:Receivables:HomeRental CNY name: "居家物业/房租押金" nondisposable: 1 2000-01-01 open Expenses:Home:Utilities name: "居家物业/水电煤费" 2000-01-01 open Expenses:Human:Family name: "人情往来/家人" 2000-01-01 open Expenses:Human:Friends name: "人情往来/朋友" 2000-01-01 open Expenses:Human:Donation name: "人情往来/捐赠" ; 五险一金 ; 失业险、工伤险、生育险、医疗险、养老险、公积金 ; (其中生育险已纳入医疗险) ; ; 1949-10-01 open Expenses:CN:YourCity:UnemploymentInsurance name: "个人缴纳的失业险" 1949-10-01 open Expenses:CN:YourCity:WorkInjuryInsurance name: "个人缴纳的工伤险" 1949-10-01 open Expenses:CN:YourCity:MedicalInsurance name: "个人缴纳的医疗保险(含生育险)" 1949-10-01 open Expenses:CN:YourCity:PensionInsurance name: "个人缴纳的养老金(只记账不坐实, 个人认为应该算支出)" 1949-10-01 open Assets:CN:YourCity:HousingProvidentFund name: "住房公积金账户(含个人和公司的基本和补充)" nondisposable: 1 1949-10-01 open Expenses:CN:YourCity:Tax name: "YourCity税" * Cash/Bank Accounts 2000-01-01 open Assets:Cash CNY,USD,JPY name: "现钞" 2000-01-01 open Assets:CN:Saving:Wechat CNY name: "微信钱包余额" 2000-01-01 open Assets:CN:Saving:Alipay CNY name: "支付宝余额" 2000-01-01 open Assets:CN:Saving:CMB CNY,USD,HKD name: "招商银行" 2000-01-01 open Income:CN:Saving:Interest CNY 2000-01-01 open Assets:CN:Saving:CCB CNY,USD,HKD name: "建设银行" 2000-01-01 open Assets:HK:Saving:CMB CNY,USD,HKD name: "招商银行香港分行" * Liabilities ; 同一家银行的多张信用卡合在一个账户结算 ; 浦发银行全币种卡会在消费时候自动购汇，还款还的人民币， ; 所以本质上是人民币计算的 2000-01-01 open Liabilities:CN:CreditCard:SPDB CNY,USD name: "浦发银行信用卡" ; 工商银行全币种卡需要收购购汇还款，因此当股票账户处理， ; 消费直接记外币，还款时先购汇再还外币 2000-01-01 open Liabilities:CN:CreditCard:ICBC "FIFO" name: "工商银行信用卡" ; 信用卡返现 2000-01-01 open Income:CN:CreditCard:SPDB CNY * Company Accounts 2000-01-01 open Assets:Receivables:YourEmployer CNY name: "应收报销" 2000-01-01 open Income:YourEmployer:BaseSalary CNY name: "税前工资" 2000-01-01 open Income:YourEmployer:HousingProvidentFund CNY name: "公司缴纳的公积金" 2000-01-01 open Income:YourEmployer:AnnualBonus CNY name: "年终奖" * Investment Accounts 2017-01-01 open Assets:Fund:TT:Positions "FIFO" name: "天天基金" 2017-01-01 open Assets:Fund:AF:Positions "FIFO" name: "蚂蚁财富(含余额宝)" 2017-01-01 open Assets:Securities:FT:Cash HKD,USD,CNH name: "富途证券现金账户(其中CNH为离岸人民币, CNY为在岸人民币)" 2017-01-01 open Assets:Securities:FT:Positions "FIFO" name: "富途证券投资组合账户" 2017-01-01 open Assets:Securities:XZ:Cash CNY name: "东方财富(西藏)证券现金账户" 2017-01-01 open Assets:Securities:XZ:Positions "FIFO" name: "东方财富(西藏)证券投资组合账户" 2017-01-01 open Income:Trade:PnL CNY,USD,HKD name: "投资盈亏" 2017-01-01 open Income:Trade:Dividen CNY,USD,HKD name: "分红" 2017-01-01 open Expenses:Trade:Fee CNY,USD,HKD name: "交易税费" 2000-01-01 open Assets:CryptoCoins:Positions "FIFO" name: "加密货币持仓" 2000-01-01 open Assets:CryptoCoins:Coinbase:Positions "FIFO" name: "加密货币交易所持仓" * Other ; LiuNeng 欠你钱 2000-01-01 open Assets:Receivables:LiuNeng CNY name: "刘能应还" ; 你欠 ZhaoSi 钱 2000-01-01 open Liabilities:Payables:ZhaoSi CNY name: "赵四应还" ================================================ FILE: ledger/commodity.beancount ================================================ * Currency 2019-01-01 commodity CNY name: "人民币" asset-class: "现金" asset-subclass: "本币" 2019-01-01 commodity CNH name: "离岸人民币" asset-class: "现金" asset-subclass: "外汇" 2019-01-01 commodity USD name: "美元" asset-class: "现金" asset-subclass: "外汇" price: "CNY:exchangeratesapi/USDCNY,yahoo/USDCNY=X" 2019-01-01 commodity JPY name: "日元" asset-class: "现金" asset-subclass: "外汇" price: "CNY:exchangeratesapi/JPYCNY,yahoo/JPYCNY=X" 2019-01-01 commodity HKD name: "港元" asset-class: "现金" asset-subclass: "外汇" price: "CNY:exchangeratesapi/HKDCNY,yahoo/HKDCNY=X" 2019-01-01 commodity BTC name: "比特币" asset-class: "另类" asset-subclass: "加密货币" price: "USD:yahoo/BTCUSD=X" 2019-01-01 commodity ETH name: "以太坊" asset-class: "另类" asset-subclass: "加密货币" price: "USD:yahoo/ETHUSD=X" 2019-01-01 commodity USDT name: "USDT" asset-class: "另类" asset-subclass: "加密货币" price: "USDT:yahoo/USDT-USD" * Symbol 2019-06-07 commodity AAPL name: "Apple Inc." asset-class: "股权" asset-subclass: "美股" price: "USD:xueqiu/US:AAPL,yahoo/AAPL" 2019-06-07 commodity SPY name: "SPDR S&P 500 ETF" asset-class: "股权" asset-subclass: "指数基金" price: "USD:xueqiu/US:SPY,yahoo/SPY" 2019-06-07 commodity HK_0700 name: "腾讯控股" asset-class: "股权" asset-subclass: "港股" price: "HKD:xueqiu/HK:00700,yahoo/0700.HK" 2019-06-07 commodity HK_2800 name: "盈富基金" asset-class: "股权" asset-subclass: "港股" price: "HKD:xueqiu/HK:02800,yahoo/2800.HK" 2019-06-07 commodity CN_F110011 name: "易方达中小盘混合" asset-class: "股权" asset-subclass: "偏股混合基金" price: "CNY:eastmoney/F110011" 2019-01-01 commodity CN_F000187 name: "华泰柏瑞丰盛纯债债券A" asset-class: "债权" asset-subclass: "债券基金" price: "CNY:eastmoney/F000187" 2019-01-01 commodity CN_510300 name: "华泰沪深300ETF" asset-class: "股权" asset-subclass: "指数基金" price: "CNY:xueqiu/CN:SH510300,yahoo/510300.SS" 2019-01-01 commodity CN_000001 name: "平安银行" asset-class: "股权" asset-subclass: "A股" price: "CNY:xueqiu/CN:SZ000001,yahoo/000001.SZ" 2019-01-01 commodity CN_128047 name: "光电转债" asset-class: "债权" asset-subclass: "可转换债券" price: "CNY:xueqiu/CN:SZ128047" ================================================ FILE: ledger/cryptocoin.beancount ================================================ 2019-07-16 * "人民币买USDT" Assets:CN:Saving:CMB -19999.95 CNY Assets:CryptoCoins:Coinbase:Positions 2877.69 USDT {6.95 CNY} 2019-07-16 * "USDT买BTC" Assets:CryptoCoins:Coinbase:Positions -1877.69 USDT Assets:CryptoCoins:Coinbase:Positions 0.17455 BTC {10757.30 USDT} 2019-07-16 * "USDT买ETH" Assets:CryptoCoins:Coinbase:Positions -223.66 USDT Assets:CryptoCoins:Coinbase:Positions 1 ETH {223.66 USDT} ================================================ FILE: ledger/daily/2019/2019-06-03-other.beancount ================================================ 2019-05-04 * "吃饭同事同事付的钱, 转给他" card: "9999" Expenses:Food:Meals 20.00 CNY Assets:CN:Saving:Wechat -20.00 CNY 2019-05-31 * "支付房租" Expenses:Home:Rental 5000 CNY Assets:CN:Saving:CMB 2019-05-29 * "借给LiuNeng5000元" Assets:Receivables:LiuNeng 5000 CNY Assets:CN:Saving:CMB 2019-05-31 * "LiuNeng还款5000元" Assets:CN:Saving:CMB Assets:Receivables:LiuNeng -5000 CNY 2019-05-29 * "向ZhaoSi借款2000元" Assets:CN:Saving:CMB 2000 CNY Liabilities:Payables:ZhaoSi 2019-05-29 * "还ZhaoSi 1999元" Assets:CN:Saving:CMB -1999 CNY Liabilities:Payables:ZhaoSi 1999 CNY 2019-05-20 * "出差吃了一顿饭" #meals #xx-trip-2019-may ; 出差吃饭花了 50 USD, 银行自动购汇 Liabilities:CN:CreditCard:SPDB -50 USD @ 6.86 CNY Assets:Receivables:YourEmployer 2019-05-20 * "出差打车" #transport #xx-trip-2019-may Liabilities:CN:CreditCard:SPDB -30 USD @ 6.85 CNY Assets:Receivables:YourEmployer 2019-05-30 * "收到出差报销" #xx-trip-2019-may Assets:Receivables:YourEmployer Assets:CN:Saving:CMB 548.50 CNY ================================================ FILE: ledger/daily/2019/2019-06-03-settle.beancount ================================================ 2019-06-30 balance Assets:CN:Saving:CMB 42430.10 CNY ================================================ FILE: ledger/daily/2019/2019-06-03-spdbcc.beancount ================================================ ;; -*- mode: beancount -*- ; 使用如下命令 ; bean-extract importers/spdccc_importer.py raw-data/spdbcc/2019-05-spdbcc.csv > ledger/daily/2019/2019-06-03-spdbcc.beancount ; 生成本文件后人工修改错误的内容 2019-05-02 * "信用卡还款" card: "9999" Liabilities:CN:CreditCard:SPDB 1230 CNY Assets:CN:Saving:CMB -1230 CNY 2019-05-03 * "支付宝 餐厅" card: "9999" Liabilities:CN:CreditCard:SPDB -44.00 CNY Expenses:Food:Meals 44.00 CNY 2019-05-03 * "京东买了个包" card: "9999" Liabilities:CN:CreditCard:SPDB -320.00 CNY Expenses:Home:Groceries 320.00 CNY 2019-05-03 * "不想要了京东退款" card: "9999" Liabilities:CN:CreditCard:SPDB 320.00 CNY Expenses:Home:Groceries -320.00 CNY 2019-05-03 * "支付宝 XX小吃" card: "9999" ; 和同事一起吃了一份人均23元的盒饭，帮同事代付， ; 同事立刻转了钱到我的微信 Liabilities:CN:CreditCard:SPDB -46.00 CNY Expenses:Food:Meals 23.00 CNY Assets:CN:Saving:Wechat 23.00 CNY 2019-05-04 * "支付宝 XX餐饮" card: "9999" Liabilities:CN:CreditCard:SPDB -152.00 CNY Expenses:Food:Meals 152.00 CNY 2019-05-04 * "支付宝 刘能" card: "9999" Liabilities:CN:CreditCard:SPDB -13.00 CNY Expenses:Food:Meals 13.00 CNY 2019-05-05 * "支付宝 中国联合网络通信有限公司" card: "9999" Liabilities:CN:CreditCard:SPDB -99.50 CNY Expenses:Comm:PhonePlan 99.50 CNY 2019-05-05 * "支付宝 XX电力公司" card: "9999" Liabilities:CN:CreditCard:SPDB -56.49 CNY Expenses:Home:Utilities 56.49 CNY 2019-05-05 * "支付宝 XX果品" card: "9999" Liabilities:CN:CreditCard:SPDB -30.00 CNY Expenses:Food:FruitSnacks 18.00 CNY note: "西瓜" Expenses:Food:FruitSnacks 12.00 CNY note: "苹果" 2019-05-06 * "支付宝 上海赵四餐饮服务有限公司" card: "9999" Liabilities:CN:CreditCard:SPDB -20.00 CNY Expenses:Food:Meals 20.00 CNY 2019-05-06 * "支付宝 谢广坤" card: "9999" Liabilities:CN:CreditCard:SPDB -22.00 CNY Expenses:Food:Meals 22.00 CNY 2019-05-06 * "支付宝 上海福满家便利有限公司" card: "9999" Liabilities:CN:CreditCard:SPDB -13.80 CNY Expenses:Food:FruitSnacks 13.80 CNY 2019-05-07 * "支付宝 北京嘀嘀无限科技发展有…" card: "9999" Liabilities:CN:CreditCard:SPDB -11.00 CNY Expenses:Transport:Taxi 11.00 CNY ================================================ FILE: ledger/daily/2019.beancount ================================================ include "2019/2019-06-03-spdbcc.beancount" include "2019/2019-06-03-other.beancount" include "2019/2019-06-03-settle.beancount" ================================================ FILE: ledger/init.beancount ================================================ ; 从当日起使用 beancount 记账，为了做平帐，初始化的资金 ; 从 Equity:Openings-Balance CNY,USD,HKD,BTC 中来 2019-01-01 * "Opening Balances" Equity:Openings-Balance ; 应收房租押金 Assets:Receivables:HomeRental 5000 CNY ; 公积金账户余额（含补充公积金） ; 公司和个人缴纳的公积金都会进这个账户 Assets:CN:YourCity:HousingProvidentFund 20000 CNY ; 现钞 Assets:Cash 1000 CNY Assets:Cash 1000 USD Assets:Cash 0 JPY Assets:CN:Saving:Wechat 123.50 CNY Assets:CN:Saving:Alipay 1233.0 CNY Assets:CN:Saving:CMB 50000 CNY Assets:HK:Saving:CMB 1000 USD Assets:HK:Saving:CMB 10000 HKD Assets:CN:Saving:CCB 10000 CNY ; 应收报销 Assets:Receivables:YourEmployer 0 CNY ; FT=富途证券 Assets:Securities:FT:Cash 100000 HKD Assets:Securities:FT:Cash 20000 USD Assets:Securities:FT:Cash 1000 CNH ; 已有 10 股 AAPL, 持仓成本价 153.39 USD Assets:Securities:FT:Positions 10 AAPL {153.39 USD} Assets:Securities:FT:Positions 10 SPY {243.315 USD} Assets:Securities:FT:Positions 100 HK_0700 {314 HKD} Assets:Securities:FT:Positions 100 HK_2800 {25.8 HKD} ; XZ=东方财富证券(西藏证券) ; 股票账户中的现金余额 Assets:Securities:XZ:Cash 10000 CNY Assets:Securities:XZ:Positions 100 CN_510300 {3.011 CNY} Assets:Securities:XZ:Positions 100 CN_000001 {9.25 CNY} Assets:Securities:XZ:Positions 100 CN_128047 {100 CNY} ; TT=天天基金 Assets:Fund:TT:Positions 10000 CN_F110011 {3.2376 CNY} Assets:Fund:TT:Positions 100 CN_F000187 {1.2088 CNY} ; AF=AntFund=蚂蚁基金 Assets:Fund:AF:Positions 4900 CN_F000187 {1.2088 CNY} ; 基金账户中的货币基金当现金(CNY)处理 Assets:Fund:AF:Positions 5000 CNY Assets:CryptoCoins:Positions 1 BTC {4102 USD} ; 信用卡欠款 Liabilities:CN:CreditCard:SPDB -1230 CNY ================================================ FILE: ledger/invest.beancount ================================================ ; 货币基金当现金处理，这和其他场外基金(如CN_F000187)处理方式不一样 ; 原因是货币基金没有净值的概念，没办法自动计算收益 2019-05-20 * "在天天基金中购买了10000元某货币基金" #money-fund Assets:Fund:TT:Positions 10000 CNY Assets:CN:Saving:CMB 2019-05-31 * "Buy 5 SPY@291.46" Assets:Securities:FT:Cash -1459.3 USD Assets:Securities:FT:Positions 5 SPY {291.46 USD} Expenses:Trade:Fee 2 USD 2019-05-31 * "富途证券 USD换HKD, 手续费 2 USD" Assets:Securities:FT:Cash -1000 USD Assets:Securities:FT:Cash 7850 HKD @ USD Expenses:Trade:Fee 2 USD 2019-05-31 * "富途证券 卖出 50 HK_0700" ; 成本价 314 HKD ; 买入金额 314 HKD * 50 = 15700 HKD ; 卖出金额 326 HKD * 50 = 16300 HKD ; 卖出手续费 38 HKD ; 金额入帐 16300 - 38 HKD = 16262 ; 投资收益(不计手续费) 16300 - 15700 = 600 HKD ; 投资收益(考虑手续费) 600 - 38 = 562 HKD Assets:Securities:FT:Cash 16262 HKD Assets:Securities:FT:Positions -50 HK_0700 {} Expenses:Trade:Fee 38 HKD Income:Trade:PnL; 此处 值位 -600 HKD 但一般不需要写会自动计算 ; CN_F000187 的价格通过 bean-price 自动获取自动计算收益 2019-05-31 * "购买债券基金 CN_F000187 (手续费千分之一)" Assets:Fund:TT:Positions 1000 CN_F000187 {1.209 CNY} Assets:CN:Saving:CMB -1210 CNY Expenses:Trade:Fee 1 CNY 2019-05-30 * "货币基金自买入之日起收益" #money-fund Assets:Fund:TT:Positions 7 CNY Income:Trade:PnL ================================================ FILE: ledger/main.beancount ================================================ option "title" "YourLedger" ; 记账时千分之一的偏差忽略不计 option "inferred_tolerance_default" "*:0.001" ; 汇总时你希望以什么货币单位结算 option "operating_currency" "CNY" option "operating_currency" "USD" option "operating_currency" "HKD" include "account.beancount" include "init.beancount" ;; 工资流水 include "salary.beancount" ;; 工资流水 include "daily/2019.beancount" ;; 标的 include "commodity.beancount" include "invest.beancount" include "prices.beancount" include "cryptocoin.beancount" ================================================ FILE: ledger/prices.beancount ================================================ 2019-07-05 price AAPL 204.229999999999989768 USD 2019-07-06 price CNH 0.9990799999999999680966311643715016543865203857421875 CNY 2019-07-05 price CN_000001 13.919999999999999929 CNY 2019-07-05 price CN_510300 3.920999999999999819 CNY 2019-07-05 price CN_F000187 1.222400000000000000 CNY 2019-07-05 price CN_F110011 5.100700000000000000 CNY 2019-07-06 price HKD 0.88380000000000003002043058586423285305500030517578125 CNY 2019-07-05 price HK_0700 359.800000000000011369 HKD 2019-07-05 price HK_2800 29.500000000000000000 HKD 2019-07-06 price JPY 0.06350000000000000088817841970012523233890533447265625 CNY 2019-07-05 price SPY 298.459999999999979536 USD 2019-07-06 price USD 6.8924000000000003041122909053228795528411865234375 CNY 2019-07-05 price CN_128047 119.290000000000006253 CNY 2019-07-07 price BTC 11213.89099999999962165020406246185302734375 USD ; TODO: crypto coin price source 2019-07-16 price USDT 1.01 USD 2019-07-16 price USDT 6.95 CNY 2019-07-16 price BTC 10757.30 USDT 2019-07-16 price ETH 223.85 USDT 2019-07-15 price AAPL 205.210000000000007958 USD 2019-07-16 price CNH 0.99919999999999997708499677173676900565624237060546875 CNY 2019-07-16 price CN_000001 13.750000000000000000 CNY 2019-07-16 price CN_128047 117.709999999999993747 CNY 2019-07-16 price CN_510300 3.853000000000000203 CNY 2019-07-16 price CN_F000187 1.223300000000000000 CNY 2019-07-15 price CN_F110011 5.038900000000000000 CNY 2019-07-16 price HKD 0.87919999999999998152588887023739516735076904296875 CNY 2019-07-16 price HK_0700 362.600000000000022737 HKD 2019-07-16 price HK_2800 29.300000000000000711 HKD 2019-07-16 price JPY 0.063659999999999994368948819101206026971340179443359375 CNY 2019-07-15 price SPY 300.750000000000000000 USD 2019-07-16 price USD 6.87650000000000005684341886080801486968994140625 CNY 2019-07-16 price AAPL 203.116099999999988768 USD 2019-07-16 price CN_F110011 4.969500000000000000 CNY 2019-07-16 price SPY 296.873100000000022192 USD 2019-07-17 price AAPL 201.973899999999986221 USD 2019-07-17 price BTC 9693.8017578125 USD 2019-07-17 price CN_000001 13.689999999999999503 CNY 2019-07-17 price CN_128047 119.000000000000000000 CNY 2019-07-17 price CN_510300 3.786799999999999944 CNY 2019-07-17 price CN_F000187 1.223400000000000000 CNY 2019-07-17 price CN_F110011 4.953100000000000000 CNY 2019-07-17 price HKD 0.880129170699999963 CNY 2019-07-17 price HK_0700 363.199999999999988631 HKD 2019-07-17 price HK_2800 29.300000000000000711 HKD 2019-07-17 price SPY 294.921699999999987085 USD 2019-07-17 price USD 6.877485510499999677 CNY 2019-07-18 price AAPL 204.268300000000010641 USD 2019-07-18 price BTC 10666.484375 USD 2019-07-18 price CN_000001 13.669999999999999929 CNY 2019-07-18 price CN_128047 118.400000000000005684 CNY 2019-07-18 price CN_510300 3.762199999999999989 CNY 2019-07-18 price CN_F000187 1.223900000000000000 CNY 2019-07-18 price CN_F110011 4.894200000000000000 CNY 2019-07-18 price HKD 0.880370547800000014 CNY 2019-07-18 price HK_0700 356.600000000000022737 HKD 2019-07-18 price HK_2800 29.149999999999998579 HKD 2019-07-18 price SPY 296.001399999999989632 USD 2019-07-18 price USD 6.880171183999999940 CNY 2019-07-19 price AAPL 201.219099999999997408 USD 2019-07-19 price BTC 10530.7275390625 USD 2019-07-19 price CN_000001 13.990000000000000213 CNY 2019-07-19 price CN_128047 118.751000000000004775 CNY 2019-07-19 price CN_510300 3.801600000000000090 CNY 2019-07-19 price CN_F000187 1.224200000000000000 CNY 2019-07-19 price CN_F110011 4.936600000000000000 CNY 2019-07-19 price HKD 0.881261341500000017 CNY 2019-07-19 price HK_0700 361.800000000000011369 HKD 2019-07-19 price HK_2800 29.449999999999999289 HKD 2019-07-19 price SPY 294.357100000000002638 USD 2019-07-19 price USD 6.878407268800000196 CNY 2019-07-22 price AAPL 205.817700000000002092 USD 2019-07-22 price BTC 10343.1015625 USD 2019-07-22 price CN_000001 13.849999999999999645 CNY 2019-07-22 price CN_128047 118.219999999999998863 CNY 2019-07-22 price CN_510300 3.771999999999999797 CNY 2019-07-22 price CN_F000187 1.224800000000000000 CNY 2019-07-22 price CN_F110011 4.934500000000000000 CNY 2019-07-22 price HKD 0.881064109200000001 CNY 2019-07-22 price HK_0700 357.600000000000022737 HKD 2019-07-22 price HK_2800 29.000000000000000000 HKD 2019-07-22 price SPY 295.080199999999990723 USD 2019-07-22 price USD 6.880784663400000056 CNY 2019-07-23 price AAPL 207.426799999999985857 USD 2019-07-23 price BTC 9900.7646484375 USD 2019-07-23 price CN_000001 13.759999999999999787 CNY 2019-07-23 price CN_128047 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chardet==3.0.4 # via beancount, requests cheroot==8.4.8 # via fava click==7.1.2 # via fava, flask, pip-tools fava==1.17 # via -r requirements.in flask-babel==2.0.0 # via fava flask==1.1.2 # via fava, flask-babel google-api-core==1.23.0 # via google-api-python-client google-api-python-client==1.12.8 # via beancount google-auth-httplib2==0.0.4 # via google-api-python-client google-auth==1.23.0 # via google-api-core, google-api-python-client, google-auth-httplib2 googleapis-common-protos==1.52.0 # via google-api-core httplib2==0.18.1 # via -r requirements.in, google-api-python-client, google-auth-httplib2, oauth2client idna==2.10 # via requests iniconfig==1.1.1 # via pytest itsdangerous==1.1.0 # via flask jaraco.functools==3.0.1 # via cheroot jinja2==2.11.2 # via fava, flask, flask-babel lxml==4.6.1 # via beancount markdown2==2.3.10 # via fava markupsafe==1.1.1 # via jinja2 more-itertools==8.6.0 # via cheroot, jaraco.functools numpy==1.19.4 # via pandas oauth2client==4.1.3 # via -r requirements.in packaging==20.4 # via pytest pandas==1.1.4 # via -r requirements.in pip-tools==5.4.0 # via -r requirements.in pluggy==0.13.1 # via pytest ply==3.11 # via beancount, fava protobuf==3.14.0 # via google-api-core, googleapis-common-protos py==1.9.0 # via pytest pyasn1-modules==0.2.8 # via google-auth, oauth2client pyasn1==0.4.8 # via oauth2client, pyasn1-modules, rsa pyparsing==2.4.7 # via packaging pytest==6.1.2 # via beancount python-dateutil==2.8.1 # via beancount, pandas python-magic==0.4.18 # via beancount pytz==2020.4 # via babel, flask-babel, google-api-core, pandas requests==2.25.0 # via -r requirements.in, beancount, google-api-core rsa==4.6 # via google-auth, oauth2client simplejson==3.17.2 # via fava six==1.15.0 # via cheroot, google-api-core, google-api-python-client, google-auth, google-auth-httplib2, oauth2client, packaging, pip-tools, protobuf, python-dateutil soupsieve==2.0.1 # via beautifulsoup4 toml==0.10.2 # via pytest uritemplate==3.0.1 # via google-api-python-client urllib3==1.26.2 # via apiclient, requests werkzeug==1.0.1 # via fava, flask # The following packages are considered to be unsafe in a requirements file: # pip # setuptools ================================================ FILE: scripts/README.md ================================================ 理论净资产 = 总资产 - 负债 净资产 = 理论总资产 - 预付款项 沉没资产 = 预付款项（房租、宽带） 可投资现金流(包含借来的钱) = 总资产 - 预付款项（房租、宽带）-不可支配款项（房租押金、住房公积金） 可投资净资产 = 可投资现金流 - 负债（应还信用卡、预收款项） 杠杆率 = 可投资现金流 / 可投资净资产 - 1 非投资收入 = 工资收入等 非投资支出 = 税、生活开销等。预付款也作为支出。比如一次性预付3个月的房租作为一笔支出。 投资盈亏 = 净资产 + 非投资收入 - 非投资支出 - 昨日净资产 投资盈亏% = 投资盈亏 / 昨日可投资净资产 ================================================ FILE: scripts/generate-networth-report.py ================================================ #!/usr/bin/env python3 """ 计算每日投资盈亏和投资净值曲线 """ import os import csv import datetime import logging import collections import io import decimal import click import beancount.loader import beancount.core.data from beancount.core import prices from beancount.ops.holdings import get_assets_holdings logger = logging.getLogger() KNOWN_ASSET_CLASSES = { "股权", "另类", "债权", "现金", } EXPENSES_PREFIX = "Expenses:" EXPENSES_TRADE_PREFIX = "Expenses:Trade:" EXPENSES_PREPAYMENTS_PREFIX = "Assets:PrePayments" def get_maps(entries): account_map = {} commodity_map = {} for entry in entries: if isinstance(entry, beancount.core.data.Open): account_map[entry.account] = entry elif isinstance(entry, beancount.core.data.Commodity): commodity_map[entry.currency] = entry return account_map, commodity_map def get_ledger_file(): this_file = os.path.abspath(__file__) workdir = os.path.dirname(this_file) while not os.path.exists(os.path.join(workdir, "ledger")): workdir = os.path.dirname(workdir) return os.path.join(workdir, "ledger", "main.beancount") def compute_networth_series(since_date, end_date=None): if end_date is None: end_date = datetime.date.today() (entries, errors, options_map) = beancount.loader.load_file(get_ledger_file()) account_map, commodity_map = get_maps(entries) target_currency = 'CNY' curr_date = since_date result = [] prev_networth = None prev_disposable_networth = None cum_invest_nav = decimal.Decimal("1.0") cum_invest_nav_ytd = decimal.Decimal("1.0") cum_invest_pnl = decimal.Decimal(0) cum_invest_pnl_ytd = decimal.Decimal(0) while curr_date <= end_date: entries_to_date = [entry for entry in entries if entry.date <= curr_date] holdings_list, price_map_to_date = get_assets_holdings( entries_to_date, options_map, target_currency ) raw_networth_in_cny = decimal.Decimal(0) # 包含sunk资产的理论净资产 networth_in_cny = decimal.Decimal(0) # 不包含sunk资产的净资产 disposable_networth_in_cny = decimal.Decimal(0) dnw_by_asset_class = {} for hld in holdings_list: if hld.currency == "DAY": continue acc = account_map[hld.account] cmdt = commodity_map[hld.currency] if hld.market_value is None: raise ValueError(hld) raw_networth_in_cny += hld.market_value # 预付但大部分情况下不能兑现的沉没资产，比如预付的未来房租 is_sunk = bool(int(acc.meta.get("sunk", 0))) if is_sunk: continue # 不可支配，比如房租押金 nondisposable = bool(int(acc.meta.get("nondisposable", 0))) if not nondisposable: disposable_networth_in_cny += hld.market_value asset_class = cmdt.meta["asset-class"] if asset_class not in dnw_by_asset_class: dnw_by_asset_class[asset_class] = decimal.Decimal(0) dnw_by_asset_class[asset_class] += hld.market_value networth_in_cny += hld.market_value txs_of_date = [ entry for entry in entries if entry.date == curr_date and isinstance(entry, beancount.core.data.Transaction) ] non_trade_expenses = decimal.Decimal(0) non_trade_incomes = decimal.Decimal(0) for tx in txs_of_date: is_time_tx = any((posting.units.currency == "DAY" for posting in tx.postings)) if is_time_tx: continue for posting in tx.postings: acc = posting.account is_non_trade_exp = ( acc.startswith(EXPENSES_PREFIX) and not acc.startswith(EXPENSES_TRADE_PREFIX) ) or ( acc.startswith(EXPENSES_PREPAYMENTS_PREFIX) ) is_non_trade_inc = acc.startswith("Income:") and not acc.startswith("Income:Trade:") if is_non_trade_exp or is_non_trade_inc: if posting.units.currency != target_currency: base_quote = (posting.units.currency, target_currency) _, rate = prices.get_latest_price(price_map_to_date, base_quote) else: rate = decimal.Decimal(1) if is_non_trade_exp: non_trade_expenses += (posting.units.number * rate) else: non_trade_incomes -= (posting.units.number * rate) if prev_networth: pnl = networth_in_cny - non_trade_incomes + non_trade_expenses - prev_networth pnl_str = ("%.2f" % pnl) if not isinstance(pnl, str) else pnl pnl_rate_str = "%.4f%%" % (100 * pnl / prev_disposable_networth) cum_invest_nav *= (1 + pnl / prev_disposable_networth) cum_invest_nav_ytd *= (1 + pnl / prev_disposable_networth) cum_invest_pnl += pnl cum_invest_pnl_ytd += pnl else: pnl = None pnl_str = 'n/a' pnl_rate_str = 'n/a' daily_status = { "日期": curr_date, # 理论净资产=总资产 - 负债 "理论净资产": "%.2f" % raw_networth_in_cny, # 净资产=总资产' - 负债（信用卡）- 沉没资产 "净资产": "%.2f" % networth_in_cny, "沉没资产": "%.2f" % (raw_networth_in_cny - networth_in_cny), # 可投资金额=净资产 - 不可支配资产（公积金、预付房租、宽带) "可投资净资产": "%.2f" % disposable_networth_in_cny, # Income:Trade(已了结盈亏、分红) 以外的 Income (包含公积金收入、储蓄利息) "非投资收入": "%.2f" % non_trade_incomes, # Expenses:Trade 以外的 Expenses (包含社保等支出) "非投资支出": "%.2f" % non_trade_expenses, "投资盈亏": pnl_str, # 投资盈亏% = 当日投资盈亏/昨日可投资金额 "投资盈亏%": pnl_rate_str, "累计净值": "%.4f" % cum_invest_nav, "累计盈亏": "%.2f" % cum_invest_pnl, "当年净值": "%.4f" % cum_invest_nav_ytd, "当年盈亏": "%.2f" % cum_invest_pnl_ytd, } if curr_date.weekday() >= 5: if pnl is not None: assert pnl <= 0.01, daily_status # 预期周末不应该有投资盈亏 assert abs(sum(dnw_by_asset_class.values()) - disposable_networth_in_cny) < 1 assert set(dnw_by_asset_class.keys()) <= KNOWN_ASSET_CLASSES, dnw_by_asset_class for asset_class in KNOWN_ASSET_CLASSES: propotion = 100 * dnw_by_asset_class.get(asset_class, 0) / disposable_networth_in_cny daily_status[f"{asset_class}%"] = f"{propotion:.2f}%" result.append(daily_status) next_date = curr_date + datetime.timedelta(days=1) if curr_date.year != next_date.year: cum_invest_nav_ytd = decimal.Decimal("1.0") cum_invest_pnl_ytd = decimal.Decimal(0) curr_date = next_date prev_networth = networth_in_cny prev_disposable_networth = disposable_networth_in_cny return result def print_portfolio_csv(rows, transpose): fhandler = io.StringIO() writer = csv.DictWriter(fhandler, fieldnames=rows[0].keys()) writer.writeheader() writer.writerows(rows) if not transpose: print(fhandler.getvalue().strip()) return transposed = list(zip(*csv.reader(io.StringIO(fhandler.getvalue())))) t_fhandler = io.StringIO() csv.writer(t_fhandler).writerows(transposed) print(t_fhandler.getvalue().strip()) def add_padding(rows): curr_date = rows[-1]["日期"] empty_row = {key: "" for key, val in rows[-1].items()} while True: curr_date += datetime.timedelta(days=1) if (curr_date.month == 1 and curr_date.day == 1): break empty_row["日期"] = "" # curr_date rows.append(empty_row.copy()) return rows @click.command() @click.option('-s', '--since', default=None) @click.option('--padding/--no-padding', default=False) @click.option('--transpose/--no-transpose', default=False) def main(since, padding, transpose): if since is None: today = datetime.date.today() since_date = datetime.date(today.year, 1, 1) else: since_date = datetime.datetime.strptime(since, "%Y-%m-%d").date() rows = compute_networth_series(since_date) if padding: rows = add_padding(rows) print_portfolio_csv(rows, transpose) if __name__ == "__main__": main() ================================================ FILE: scripts/generate-portfolio.py ================================================ #!/usr/bin/env python3 """ 本脚本用来生成持仓CSV, 后续可以把CSV导入表格软件进一步聚合分析。 和 bean-report 相比主要的优先是： - 输出带 meta 中自定义的名称，资产类别 - 过滤已支出不可退款的，预付款项 - 过滤不可支配资产 """ import os import csv import datetime import logging from decimal import Decimal import io import click import beancount.loader import beancount.core.data from beancount.core import getters from beancount.ops.holdings import get_assets_holdings logger = logging.getLogger() def get_account_map(entries): account_map = {} for entry in entries: if isinstance(entry, beancount.core.data.Open): account_map[entry.account] = entry return account_map def sort_key(row): """ 输出大体的风险系数以供排序 """ asset_class = row["一级类别"] asset_subclass = row["二级类别"] ac_list = ["现金", "债券", "债权", "基金", "股票", "股权", "另类资产", "另类"] asc_list = [ "本币", "外汇", "债券基金", "可转换债券", "指数基金", '偏债混合基金', "偏股混合基金", "A股", "中国股票", "港股", "香港股票", "美股", "美国股票", "贵金属", "加密货币", ] factor1 = ac_list.index(asset_class) factor2 = asc_list.index(asset_subclass) return (1 + factor1) * 100 + factor2 def get_ledger_file(): this_file = os.path.abspath(__file__) workdir = os.path.dirname(this_file) while not os.path.exists(os.path.join(workdir, "ledger")): workdir = os.path.dirname(workdir) return os.path.join(workdir, "ledger", "main.beancount") def get_portfolio_matrix(asof_date=None): """ 打印持仓 Args: asof_date: 计算该日为止的持仓, 避免未来预付款项影响。 """ if asof_date is None: asof_date = datetime.date.today() (entries, errors, option_map) = beancount.loader.load_file(get_ledger_file()) entries = [entry for entry in entries if entry.date <= asof_date] assets_holdings, price_map = get_assets_holdings(entries, option_map) account_map = get_account_map(entries) commoditiy_map = getters.get_commodity_directives(entries) holding_groups = {} for holding in assets_holdings: if holding.currency == "DAY": continue account_obj = account_map[holding.account] if account_obj is None: raise ValueError(f"account is not defined for {holding}") currency_obj = commoditiy_map[holding.currency] if currency_obj is None: raise ValueError(f"commoditiy is not defined for {holding}") if bool(int(account_obj.meta.get("sunk", 0))): logger.warning(f"{account_obj.account} is an sunk. Ignored.") continue if bool(int(account_obj.meta.get("nondisposable", 0))): logger.warning(f"{account_obj.account} is nondisposable. Ignored.") continue for meta_field in ("name", "asset-class", "asset-subclass"): if meta_field not in currency_obj.meta: raise ValueError( "Commodity %s has no '%s' in meta" "" % (holding.currency, meta_field) ) account_name = account_obj.meta.get("name") if not account_name: raise ValueError("Account name not set for %s" % holding.account) account_nondisposable = bool(int(account_obj.meta.get("nondisposable", 0))) symbol_name = currency_obj.meta["name"] asset_class = currency_obj.meta["asset-class"] asset_subclass = currency_obj.meta["asset-subclass"] symbol = holding.currency currency = holding.cost_currency price = holding.price_number price_date = holding.price_date if price is None: if symbol == currency: price = 1 price_date = '' qty = holding.number if currency == "CNY": cny_rate = 1 else: cny_rate = price_map[(currency, "CNY")][-1][1] holding_dict = { "account": account_name, "nondisposable": account_nondisposable, "symbol": symbol, "symbol_name": symbol_name, "asset_class": asset_class, "asset_subclass": asset_subclass, "quantity": qty, "currency": currency, "price": price, "price_date": price_date, "cny_rate": cny_rate, # optional: # book_value # market_value # # chg_1 # chg_5 # chg_30 } hld_prices = price_map.get((holding.currency, holding.cost_currency)) if hld_prices is not None and holding.cost_number is not None: holding_dict["book_value"] = holding.book_value holding_dict["market_value"] = holding.market_value for dur in (1, 2, 7, 30): if len(hld_prices) < dur: continue base_date = asof_date - datetime.timedelta(days=dur) latest_price = hld_prices[-1][1] base_pxs = [(dt, px) for dt, px in hld_prices if dt <= base_date] if base_pxs: base_price = base_pxs[-1][-1] # O(N)! holding_dict[f"chg_{dur}"] = latest_price / base_price - 1 else: holding_dict[f"chg_{dur}"] = 'n/a' group_key = (symbol, account_nondisposable) holding_groups.setdefault(group_key, []).append(holding_dict) rows = [] cum_networth = 0 for (symbol, account_nondisposable), holdings in holding_groups.items(): qty_by_account = {} total_book_value = Decimal(0) total_market_value = Decimal(0) for holding in holdings: if holding["account"] not in qty_by_account: qty_by_account[holding["account"]] = 0 qty_by_account[holding["account"]] += holding["quantity"] if "book_value" in holding: total_book_value += holding["book_value"] total_market_value += holding["market_value"] if total_book_value == 0: pnlr = "n/a" else: pnlr = "%.4f%%" % ((total_market_value / total_book_value - 1) * 100) total_qty = sum(qty_by_account.values()) hld_px = holding["price"] if hld_px is None: raise ValueError(f"price not found for {holding}") networth = holding["cny_rate"] * hld_px * total_qty cum_networth += networth row = { "一级类别": holding["asset_class"], "二级类别": holding["asset_subclass"], "标的": holding["symbol_name"], "代号": symbol, "持仓量": "%.3f" % total_qty, "市场价格": "%.4f" % holding["price"], "报价日期": holding["price_date"], "市场价值": int(round(holding["price"] * total_qty)), "货币": holding["currency"], "人民币价值": "%.2f" % networth, "持仓盈亏%": pnlr, } for optional_col, col_name in [ ("chg_1", "1日%"), ("chg_2", "2日%"), ("chg_7", "7日%"), ("chg_30", "30日%") ]: if optional_col not in holding or holding[optional_col] == 'n/a': row[col_name] = "n/a" else: row[col_name] = "%.2f%%" % (holding[optional_col] * 100) rows.append(row) rows.sort(key=sort_key) for row in rows: pct = Decimal(row["人民币价值"]) / cum_networth row.update({ "占比": "%.2f%%" % (100 * pct) }) return rows, cum_networth def print_portfolio_csv(rows): fhandler = io.StringIO() writer = csv.DictWriter(fhandler, fieldnames=rows[0].keys()) writer.writeheader() writer.writerows(rows) print(fhandler.getvalue().strip()) @click.command() @click.option('-d', '--date', default=None) def main(date): logging.basicConfig(level=logging.INFO) if date is None: asof_date = datetime.date.today() else: asof_date = datetime.datetime.strptime(date, "%Y-%m-%d").date() rows, cum_networth = get_portfolio_matrix(asof_date) logger.info("As of %s, disposable networth=%d CNY", asof_date, cum_networth) print_portfolio_csv(rows) if __name__ == "__main__": main() ================================================ FILE: scripts/update-prices.py ================================================ #!/usr/bin/env python3 import os import sys import datetime ONE_DAY = datetime.timedelta(days=1) ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) PRICE_PATH = os.path.join(ROOT_DIR, "ledger", "prices.beancount") def yield_date_range(start_date, end_date): curr_date = start_date while curr_date <= end_date: if curr_date.weekday() < 5: yield curr_date curr_date += ONE_DAY def main(argv): today_only = False if len(argv) > 1 and argv[1] == "--today-only": today_only = True with open(PRICE_PATH, "rb") as fhandler: fhandler.seek(-1000, os.SEEK_END) last_line = fhandler.readlines()[-1] last_date_str = last_line.split()[0].decode() last_date = datetime.datetime.strptime(last_date_str, "%Y-%m-%d") print("echo > ledger/latest-prices.beancount") # 部分香港基金的净值更新时间比较慢，所以此处不用 last_date + 1 start_date = last_date utc_now = datetime.datetime.utcnow() end_date = utc_now for curr_date in yield_date_range(start_date, end_date): if curr_date.date() == utc_now.date(): suffix = f"| grep {curr_date:%Y-%m-%d} > ledger/latest-prices.beancount" else: suffix = f">> ledger/prices.beancount" if not today_only or curr_date.date() == utc_now.date(): print( f"PYTHONPATH=`pwd`/sources bean-price --no-cache -d {curr_date:%Y-%m-%d}" f" ledger/main.beancount {suffix};" ) def get_existed_symbol_dates(target_symbol): existed_date = set() with open(PRICE_PATH) as fhandler: for line in fhandler.readlines(): dt, _, symbol, px, unit = line.split() if symbol != target_symbol: continue existed_date.add(dt) return existed_date if __name__ == "__main__": main(sys.argv) ================================================ FILE: sources/eastmoney.py ================================================ import time import re import logging import json import requests from dateutil import tz,utils from datetime import datetime from urllib import error from math import log10, floor from beancount.core.number import D from beancount.prices import source from beancount.utils import net_utils CN_TZ = tz.gettz("Asia/Shanghai") class Source(source.Source): """ 东方财富天天基金基金净值 注意：需要在雪球标的前加F(方便区分基金与其他标的) PYTHONPATH=`pwd`/sources bean-price --no-cache -e CNY:eastmoney/F110011 """ http = requests.Session() def get_historical_price(self, ticker, date): return self._get_daily_price(ticker, date) def get_latest_price(self, ticker): return self._get_daily_price(ticker) def _get_daily_price(self, fund, date=None): assert fund[0] == "F" params = { "callback": "thecallback", "fundCode": fund[1:], "pageIndex": 1, "pageSize": 1, } if date is not None: dt_str = date.strftime("%Y-%m-%d") params.update({ "startDate": dt_str, "endDate": dt_str, }) resp = self.http.get( "https://api.fund.eastmoney.com/f10/lsjz", params=params, headers={ "Referer": "http://fundf10.eastmoney.com/jjjz_{fund}.html" } ) assert resp.status_code == 200, resp.text result_str = next(re.finditer("thecallback\((.*)\)", resp.text)).groups()[0] result = json.loads(result_str) records = result["Data"]["LSJZList"] if len(records) == 0: return trade_date = records[0]["FSRQ"] nav = D(records[0]["DWJZ"]).quantize(D('1.000000000000000000')) trade_date = datetime.strptime(trade_date, "%Y-%m-%d") trade_date = utils.default_tzinfo(trade_date, CN_TZ) return source.SourcePrice(nav, trade_date, 'CNY') ================================================ FILE: sources/exchangeratesapi.py ================================================ import time import json import requests from dateutil import tz,utils from datetime import datetime from beancount.core.number import D from beancount.prices import source class Source(source.Source): """ PYTHONPATH=`pwd`/sources bean-price --no-cache -e CNY:exchangeratesapi/USDCNY """ http = requests.Session() def get_historical_price(self, ticker, date=None): return self._get_daily_price(ticker, date) def get_latest_price(self, ticker): return self._get_daily_price(ticker) def _get_daily_price(self, ticker, date=None): assert len(ticker) == 6, ticker base = ticker[:3] symbol = ticker[3:] if date is None: date_str = "latest" else: date_str = date.strftime("%Y-%m-%d") resp = self.http.get( "https://api.exchangeratesapi.io/" + date_str, params={ "symbols": symbol, "base": base, } ) result = resp.json() close_price = D(result["rates"][symbol]).quantize(D('1.000000000000000000')) trade_date = utils.default_tzinfo( datetime.strptime(result["date"], "%Y-%m-%d"), tz.UTC ) currency = base return source.SourcePrice(close_price, trade_date, currency) ================================================ FILE: sources/xueqiu.py ================================================ import time import json import requests from dateutil import tz,utils from datetime import datetime from beancount.core.number import D from beancount.prices import source EXPECTED_COLS = [ "timestamp", "volume", "open", "high", "low", "close", "chg", "percent", "turnoverrate", "amount", "volume_post", "amount_post" ] CN_TZ = tz.gettz("Asia/Shanghai") NY_TZ = tz.gettz("America/New_York") class Source(source.Source): """ 雪球 A股、港股、美股 注意：需要在雪球标的前加国家(方便区分时区) PYTHONPATH=`pwd`/sources bean-price --no-cache -e CNY:xueqiu/CN:SH510300 PYTHONPATH=`pwd`/sources bean-price --no-cache -e HKD:xueqiu/HK:02800 PYTHONPATH=`pwd`/sources bean-price --no-cache -e USD:xueqiu/US:SPY """ http = requests.Session() headers = requests.utils.default_headers() headers.update( { 'User-Agent': ('Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_3) ' 'AppleWebKit/537.36 (KHTML, like Gecko) ' 'Chrome/73.0.3683.103 Safari/537.36'), } ) http.get("https://xueqiu.com/", headers=headers) def get_historical_price(self, ticker, date): return self._get_daily_price(ticker, date) def get_latest_price(self, ticker): return self._get_daily_price(ticker) def _get_daily_price(self, ticker, date=None): region, symbol = ticker.split(":", 1) if region in {"HK", "CN"}: exchange_tz = CN_TZ if region == "HK": currency = "HKD" else: currency = "CNY" else: assert region == "US" exchange_tz = NY_TZ currency = "USD" if date is None: trade_date = utils.default_tzinfo( datetime.now(), exchange_tz, ) else: trade_date = utils.default_tzinfo( datetime.combine(date, datetime.max.time()), exchange_tz ) begin = int(time.mktime(trade_date.timetuple())) * 1000 url = ( f"https://stock.xueqiu.com/v5/stock/chart/kline.json?" f"symbol={symbol}&begin={begin}&period=day&" f"type=before&count=-1&indicator=kline" ) resp = self.http.get(url, headers=self.headers) assert resp.status_code == 200, resp.text result = resp.json() assert result["error_code"] == 0, result["error_description"] bar = result["data"]["item"][0] assert result["data"]["column"] == EXPECTED_COLS returned_ts = bar[EXPECTED_COLS.index("timestamp")] close_price = D( bar[EXPECTED_COLS.index("close")] ).quantize(D('1.000000000000000000')) trade_date = datetime.fromtimestamp(returned_ts/1000, exchange_tz) return source.SourcePrice(close_price, trade_date, currency)